In today’s global economy, supply chains are the backbone of manufacturing processes. However, they are highly very vulnerable to disruptions, whether that’s due to natural disasters, geopolitical tensions, or unforeseen global crises. These disruptions often have a domino effect and lead to shortages of critical parts, delayed or cancelled deliveries, and unpredictable consequences for production and logistics. In response to these challenges, NARRATE offers a solution that looks ahead to the future using cutting-edge technologies such as artificial intelligence (AI), big data, digital twins and the Industrial Internet of Things (IIoT).
The aim of this project is to make supply chains more flexible, agile, resilient, and able to adapt to changing circumstances. But as promising as AI-driven manufacturing is, it’s important to understand that artificial intelligence has two sides. It has huge potential, but if it is misused, it can lead to devastating consequences.
When we talk about AI in manufacturing, it’s easy to think of the different possibilities it can give us to optimise costs: machines that learn from data, processes that self-optimize, and entire production lines that run with minimal human intervention. However, AI is only as good as the data it processes and the goals it is programmed to achieve. A badly designed AI system can increase existing inefficiencies, or even make critical decisions that damage supply chains.
Some companies rely too much on AI to make decisions without checking they are the right ones. But automated decisions could prioritise short-term profits over long-term sustainability, leading to adopt unethical decisions in the supply chain, the exploitation of vulnerable labour markets, or environmentally damaging shortcuts. AI algorithms could make supply chain more vulnerable by focusing on cost-cutting measures that make the system less resilient.
On top of that, AI models that are built on incomplete or biased data can lead to the wrong decisions being made. For example, in times of crisis, AI that doesn’t consider social and environmental factors could divert supply chains through politically unstable regions or ignore ethical sourcing guidelines. If AI is misused, it won’t help us create agile and resilient networks, it could worsen problems and increase supply chains vulnerabilities.
NARRATE is about avoiding risks and making the most of AI and does this by taking a holistic, data-driven approach. At the heart of this project is the development of an Intelligent Manufacturing Custodian (IMC) and AI platform to manage Smart Manufacturing Networks (SMN). This framework of supply chain management will use data from different sources (products, production, supply chain, machines, sensors and IoT devices) to make proactive decisions from possible offered alternatives for supply chain resilience.
The project aims for full integration, where machine learning and digital-twins model complex manufacturing processes and predict disruptions before they occur. If there is political conflict in a region where raw materials are sourced, the IMC will flag the risk, find alternative suppliers will also consider the logistics. AI is not making decisions, but giving human operators the information they need to make informed decisions.
AI isn’t just about making things more efficient. It’s about building supply chains that can recover quickly when things go wrong. AI helps companies keep a steady production flow and adapt to market changes by predicting problems and fixing them before they cause big issues. Big data and IIoT give us a better view of the whole supply chain, from factories to shipping, while digital twins let us test ideas in a virtual setting before trying them out in the real world. This is how NARRATE applies AI in its most beneficial form, focusing on building resilience and sustainability into the very fabric of manufacturing networks and not just on maximizing output.
The future of manufacturing depends on us using AI responsibly. NARRATE is a great example of how AI can be used to solve real-world problems, such as supply chain fragility. By embedding ethical principles into AI systems – prioritising transparency, sustainability, and human oversight – this project shows us how technology can be used to do good. We’ve seen what happens when AI is used without any checks and balances. There have been biased algorithms in hiring, data privacy violations, and unintended consequences of autonomous systems. Manufacturing can’t afford to make the same mistakes. That’s why NARRATE is so important. It’s not just about integrating the latest technologies, but doing so in a way that ensures the integrity and resilience of supply chains taking into account data confidentiality, which ultimately benefits society at large.
It is important to make sure that NARRATE AI models that powers these intelligent networks are transparent and accountable. AI should be a tool to help human decision-makers, not replace them. The success of this project depends on our ability to balance automation with human intuition, ensuring that the technology enhances, rather than diminishes, the agility and adaptability of global manufacturing processes.
In conclusion, AI can introduce new risks into manufacturing networks, but NARRATE shows that, when used responsibly, AI can be good even if we combine it with other advanced technologies such as digital twins or IIoT. This project will help make global manufacturing more resilient, agile and sustainable. It will help the industry cope with unpredictable disruptions. The key is to use technology carefully, prioritizing resilience, ethics and to a long-term value over the short-terms benefits.
Authors

Amparo Roca de Togores López
With contributions from Maria Jose Nuñez Ariño